What can be said about loudness?


Loudness across countries


This boxplot demonstrates the range of loudness in each country’s corpora. It somewhat mimics the relation observed on the energy feature from the very first figure. What is interesting is that most song from Bulgaria seem to be the loudest – as its least loud song is louder than all means of other countries. This may have contributed to the random forest matrix’s enhanced classification of these songs. Overall, Serbia and Greece share a relatively similar mean loudness, as well as Alania and Turkey. This also somewhat reflects the cultural division of the Balkans.

What insights can we gain from observing different audio features on track level?


Timbre and Chroma Analysis of Structure


This slide is devoted to music structure analysis of the most popular songs from the corpus, each chosen from a different country. To fully understand the structure of these songs and their comparability, we need to observe both the pitch- and timbre-based self-similarity matrices. In the case of the first song “Genge” by Relja ft. Rasta, the chroma-based similarity matrix shows small squares which indicate the ongoing switch between two chords that follows the whole song. The bridge can also be observed around 100s, as the pattern seems to be broken there. The timbre-based similarity matrix showcases repetitions more clearly, as there are three segments with the bridge dividing the second and the third. The division between the first and the second is clearly seen at around 50s, as the lines correspond to the small percussion bridge which affects both pitch and timbre. The second song “Chupki v krusta” by Fiki showcases more complex structure, as observed on the timbre-based self-similarity matrix. No clear repetitions are traced, rather the places of homogeneity, which are usually prompted by the interchange of singing and instrumental parts. The pitch-based self-similarity matrix showcases one change of the dominant pitch features. The Greek representative “Gia Ton Idio Anthropo Milame” by Vasilis Karras showcases a clear structure. The pitch-based self-similarity matrix showcases the structure that corresponds to the verse and chorus and which is repeated two times. The timbre-based self-similarity matrix complements the structure and showcases that the track starts with instrumental, then goes on to be sung by individual voices. The chorus is first sung in polyphony and then the melody is repeated in an instrumental form. Thus, the chorus itself corresponds to two large squares in the pitch matrix, as there seems to be no difference between singing and the instrumental with regards to pitch. As opposed to this song, the structure of the Turkish representative song “Askin Olayim” by Simge is more clearly observed in the timbre-based self-similarity matrix. Two big squares correspond to the singing part, while the smaller ones correspond to the instrumental. The pitch-based similarity matrix is somewhat more complex, yet it clearly demonstrates the bridge at around 130s. The last song, “Adrenalina” by Dhurata Dora seems to be the hardest to interpret, as both its matrices do not reflect musical structure that well. Yet, certain indicators are visible, as for instance, the clear novelty at around 140s. All in all, this music structure analysis of most popular songs serves to demonstrate that some patterns can be traced. The segmentations is done in a similar way, as songs from Serbia, Turkey and Greece demonstrate a very similar structure. While this can be said for a wider scope of popular music, it is still important that most popular songs from this region share a demonstratable commonality.

Is there a relationship between tempo and popularity?


Tempo and popularity in Balkan music


As stated in the beginning, one of the most distinctive features of music from this region is the rhythm and its overall temporal dimension. This plot demonstrates the relationship between tempo and popularity of selected songs. There seems to be a clear trend for favouring the 90-100BPM tempo, as the points seem to be most dense there in all countries. In Bulgaria, there seems to be another preference for 1500BPM. However, the domain of popular music in all of these countries seems to depend on a somewhat versatile tempos, which again may be brought back to the danceability of these corpora. For the danceability to be favourable feature of these cultures, there needs to be an interdependence of songs in order for them to prompt novelties which are required for people to dance to. It can also be said that the songs that score higher on the popularity scale are more often rated more danceable than not, which is also an observation that supports the hypothesis.

Summary



To what extent does music of different Balkan countries manifest the homogeneity of taste across this region?

This dashboard showcased several perspectives which shed light on the differences and similarities between Balkan popular music. Certain trends could be observed both on country level features which generally represent the selection of popular songs, as well as on track level features which represent the songs which scored the highest on the popularity index. If these corpora and representative tracks are taken as reflection of taste from these country’s listeners, than it can be argued that geographical proximity compensates for at least some of the cultural differences among these countries. Simple harmony and structure, danceability and tempo versatility as well as comparable loudness between pairs of countries can serve as a proof that some features are indeed similar. On the other hand, dendrogram and random forest matrix showcase that certain corpora are more distinguished based on audio features, which to some extent rebuffs their overall homogeneity. In conclusion, this dashboard demonstrated a template for analysing Balkan popular music, which can be further enhanced by choosing different sets of corpora, which would showcase more perspectives on music from this region and enhance the overall scientific body of knowledge on this topic.

Playlists:

  1. https://open.spotify.com/embed/playlist/16YmGXTlJgsXKjJ7vdlztn?utm_source=generator

  2. https://open.spotify.com/embed/playlist/4YM5NoxSLOpl2VmJEwZBVY?utm_source=generator

  3. https://open.spotify.com/embed/playlist/3II2lVlx382McktFzK3hgj?utm_source=generator

  4. https://open.spotify.com/embed/playlist/41G4yjL1cUJblYk6HGRLpR?utm_source=generator

  5. https://open.spotify.com/embed/playlist/3gKQ6E9Ivq7jgF8YoIddmW?utm_source=generator